CN110118382A - General operation regulation strategy identification and evaluation method for heat exchange station - Google Patents
General operation regulation strategy identification and evaluation method for heat exchange station Download PDFInfo
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Abstract
The invention discloses a general operation regulation strategy identification and evaluation method for a heat exchange station. And adopting a data mining method of unsupervised clustering. The method is based on the energy conservation law and the heat balance relation of a centralized heating system, and comprises the steps of clustering Gaussian mixture models of the three characteristics of outdoor temperature, secondary water supply temperature and secondary heat consumption one by one, dividing an unsupervised clustering result into heating time periods, and identifying a primary side strategy, a secondary side strategy, heat consumption and unit temperature difference heat consumption in different heating time periods. And finally, performing energy-saving potential evaluation on the operation regulation control strategy of the heat exchange station through heat consumption and unit temperature difference heat consumption. The unsupervised clustering data mining method is applied to actual time-by-time operation data of the heat exchange stations of the central heating system, a relatively universal operation regulation strategy identification and evaluation method is provided for different heat exchange stations, and reliable reference experience can be provided for operation optimization and energy-saving evaluation of the heat exchange stations.
Description
Technical field
The invention belongs to central heating runing adjustment control technology fields, and in particular to a kind of operation tune that heat exchange station is general
Save tactful identification and evaluation method.
Background technique
With the continuous propulsion of China's economic growth and urbanization process, energy demand structure constantly makes the transition.Central heating
Energy saving of system transformation, a large amount of informatization, it is intended to realize ' wisdom ' heat supply.But central heating system operational management exists
Problems, with the continuous complaint of hot resident, high for thermal energy consumption, the system failure emerges one after another.Wherein heat exchange station is run
Adjusting is the main problem for perplexing operational management and realizing ' wisdom ' heat supply.
As the major parameter that heat exchange station secondary side is adjusted, the rational of supply water temperature is to realize heat supply running fining
The key of adjusting.From positive theory analysis angle, domestic and foreign scholars propose and correct the fundamental formular for thermal conditioning.Engineer application
Heat supply running is usually formulated by two parameters of easily controlled secondary water-supply temperature and circular flow adjusts strategy.Also have logical
Influence of the variation for analyzing the parameters such as circular flow, radiator area, room temperature to supply water temperature adjustment curve is crossed to formulate
Adjust strategy.Since the actual characteristic of heating system, energy supply object is multifarious, formulate in entire Heating Season reasonably for water temperature
Degree runing adjustment mode is still a difficult point.
Nowadays a large amount of heat supply informatization, provides operation data abundant, these data are that operating experience is fine
Carrier.
Summary of the invention
Purpose of the invention is to overcome the shortcomings in the prior art, provides a kind of runing adjustment plan that heat exchange station is general
Slightly identification and evaluation method, by incorporating the technology of gauss hybrid models cluster data mining in heating field, this method is suitable for
Central heating system heat exchange station runs control technology field, and provides reliably for the optimization operation of heating system, Evaluation on Energy Saving
With reference to.Reliable Experience can be provided for heat exchange station operational management, reducing energy consumption, performance evaluation.
The purpose of the present invention is what is be achieved through the following technical solutions:
Claim is perfect herein after determining
Compared with prior art, the beneficial effects brought by the technical solution of the present invention are as follows:
1, the present invention is based on the thermal balance relationship in law of conservation of energy and central heating system, to outdoor temperature, secondary
Supply water temperature, three features of secondary heat consumption by when data use gauss hybrid models clustering, by Unsupervised clustering knot
Distribution of the fruit in secondary water-supply temperature-time sequence divides heating duration section, then identifies the primary side of different heating duration sections
Tactful (supply water temperature, one cycle flow), secondary side strategy (secondary water-supply temperature, secondary cycle flow) and heat dissipation
Amount, unit temperature difference heat consumption；Finally realize heat exchange station runing adjustment tactical comment.
2, compared with existing runing adjustment strategy forward direction theoretical analysis method, the present invention has more engineer application, Statistical,
Easy to operate, replicability is strong.With the more difficult heating system applied to practical individual difference of theoretical analysis method to the forward, confession
Energy object, popularization are come.The present invention proposes a kind of operation that heat exchange station is general by the Historical Monitoring data analysis of exchange heat stations
Adjust tactful identification and evaluation method.It can be diagnosed to be the inefficient and efficient strategy of heat exchange station, find soft fault existing for heat exchange station, it is soft
Failure refers to the operation reserve problem of heat exchange station.Reliable experience is provided for heat exchange station operational management, reducing energy consumption, performance evaluation to borrow
Mirror.
3, heat exchange station running optimizatin, Energy efficiency evaluation may be implemented using method of the invention.
Based on heat consumption, the secondary operation reserve of characteristic evaluating based on unit temperature difference heat consumption finds fallback strategy；
It is realized simultaneously based on unit temperature difference heat consumption a reference value and fractional energy savings is calculated to each operation reserve, amount of energy saving and divergence indicator are commented
Valence.The operation reserve of heat exchange station low cost can be instructed to diagnose and reducing energy consumption Potential Evaluation.
4, the present invention is versatile, and engineer application is wide.It is not only applicable to secondary water-supply temperature；Runing adjustment control
Various heat exchange station adjusts the adjusting of the matter such as control to the control of secondary return water temperature runing adjustment, secondary cycle flow, amount is adjusted, matter
The heat exchange station that amount regulative mode adjusts strategy is all suitable for.It is also applied for district boiler room runing adjustment strategy identification and evaluation simultaneously.
Furthermore the present invention is based on the most wide secondary water-supply temperature of engineer application to adjust control, secondary cycle flow control by stages mode
Heat exchange station specific embodiment is explained in detail.
Detailed description of the invention
Fig. 1 is heat exchange station operation reserve identification and evaluation thinking schematic diagram of the present invention.
Fig. 2 is secondary water-supply temperature operation control method theoretical diagram.
Fig. 3 is that the secondary water-supply temperature of the classification information containing cluster changes adjustment curve with outdoor temperature.
Fig. 4 is that the secondary heat consumption of the classification information containing cluster changes adjustment curve with outdoor temperature.
Fig. 5 is the associated change scatter plot of first and second supply water temperature.
Fig. 6 is that a supply water temperature of the classification information containing cluster changes adjustment curve with outdoor temperature.
Fig. 7 is one cycle flow timing variations scatter plot.
Fig. 8 is secondary cycle flow timing variations scatter plot.
Fig. 9 is the secondary water-supply temperature-time Sequence dot plot of the classification information containing cluster.
Figure 10-1 to Figure 10-4 is the 2nd class operational mode series of drawing of In The Initial Period Of Heating.
Figure 11-1 to Figure 11-4 is the 3rd class operational mode series of drawing of In The Initial Period Of Heating.
Figure 12-1 to Figure 12-4 is the 1st class operational mode series of drawing of In The Initial Period Of Heating.
Figure 13-1 to Figure 13-4 is heating the 1st class operational mode series of drawing of mid-term.
Figure 14-1 to Figure 14-4 is heating the 3rd class operational mode series of drawing of mid-term.
Figure 15-1 to Figure 15-4 is heating the 2nd class operational mode series of drawing of latter stage.
Specific embodiment
The present invention is described in further detail below in conjunction with the drawings and specific embodiments.It should be appreciated that described herein
Specific embodiment be only used to explain the present invention, be not intended to limit the present invention.
A kind of runing adjustment strategy identification and evaluation method that heat exchange station is general of the present invention, including the following steps:
Step (1): operation data gauss hybrid models are clustered；Select heating season by when outdoor temperature, secondary water-supply temperature
The data of three kinds of degree, secondary heat consumption features cluster its scatterplot data application multidimensional gauss hybrid models；
Step (2): the secondary water-supply temperature-time Sequence dot plot distribution of the classification information containing cluster is obtained；By that will cluster
Classification information is attached to color range item, is applied to secondary water-supply temperature-time Sequence dot plot；Obtain heating season various time points pair
The secondary water-supply temperature runing adjustment mode answered, one kind are one mode；
Step (3): heating duration section is divided；The characteristics of being clustered according to secondary water-supply temperature-time Sequence dot plot；Exchange
2~4 heating periods of heat stations heating season point；
Step (4): the operation reserve and heat dissipation mode in each heating period are identified；To each heating period operation reserve and
Cluster classification information is attached in each sample data, and is applied to-supply water temperature of outdoor temperature by heat dissipation pattern analysis
Scatter plot, outdoor temperature-secondary water-supply temperature scatter plot, the secondary heat consumption scatter plot of outdoor temperature-, the secondary temperature of outdoor temperature-
Poor heat consumption scatter plot obtains the heat exchange station operation reserve and heat dissipation mode under outdoor temperature reset feature；
Step (5): secondary side runing adjustment tactical comment；Linear character or number based on the secondary heat consumption of outdoor temperature-
Characteristic evaluating secondary side operation reserve according to statistics, the data statistical characteristics evaluation two based on the secondary temperature difference heat consumption of outdoor temperature-
Secondary side operation reserve calculates fractional energy savings, amount of energy saving, divergence indicator by setting temperature difference heat consumption a reference value, evaluates secondary operation
Tactful energy-saving potential and heat dissipation departure degree.
Embodiment: a kind of runing adjustment strategy identification and evaluation method that heat exchange station is general, wherein identification and evaluation Method And Principle
As shown in Figure 1.On the basis of being based on real data, closed in accordance with the thermal balance in law of conservation of energy and central heating system
System.According to principle interpretive analysis, heat exchange station heat source side to secondary side is interpreted from two levels, i.e. adjustment curve and controlling party
Formula.
It in adjustment curve level, is mainly reflected in how supply water temperature responds change of external conditions, is from heat supply theoretically
How amount responds the variation relation that change of external conditions obtains heating load and outdoor temperature, and linear relationship is presented under normal circumstances.
Under the quality adjustment mode for changing flow stage by stage, the relationship that supply water temperature changes with outdoor temperature is reenacted.It is wherein common
Weather compensation strategy be exactly supply water temperature changes and linear change with outdoor temperature be most widely used in engineering, but it is real
Border operation will consider several factors, such as In The Initial Period Of Heating charge, suddenly cooling, morning and evening special time period is specific uses heat demand.
In control mode level, it is mainly reflected in the implementation of supply water temperature variation, i.e. secondary water-supply temperature is with primary
The changing rule of side active adjustment parameter (supply water temperature, one cycle flow).Conventional secondary water-supply temperature controlling party
Formula is as shown in Figure 2, on the one hand, heat source side can carry out a matter with outdoor temperature and adjust to make secondary water-supply temperature also with outdoor temp
Degree changes and changes；On the other hand, regulating device also can be set in heat exchange station, according to outdoor temperature or other factors adjustable plate
Primary side motor-driven valve is changed, changes primary side flow, and then change secondary water-supply temperature, reaches the secondary water-supply temperature change of setting
Curve.Also side light, secondary water-supply temperature curve are on the basis of a temperature curve, and variation one cycle flow obtains
, it is verified by supply water temperature of Analysis on monitoring data with secondary water-supply temperature relation.
Using gauss hybrid models clustering outdoor temperature, secondary water-supply temperature, three features of secondary heat consumption by
When data, distribution of the Unsupervised clustering result in secondary water-supply temperature-time sequence is divided into heating duration section, then identify
The primary side strategy (supply water temperature, one cycle flow) of different heating duration sections, secondary side strategy (secondary water-supply temperature
Degree, secondary cycle flow) and heat consumption, unit temperature difference heat consumption.Finally realize heat exchange station runing adjustment tactical comment.Data
From the historical data of heat exchange station heating season actual monitoring, accuracy and operability with higher.The present embodiment will have
The method announcement that gymnastics work is implemented is as follows, is specifically divided into gauss hybrid models clustering method, data statistical analysis method.
(1) operation data gauss hybrid models are clustered
The present invention -2016 years 2015 Heating Seasons 122 of certain heat exchange station in Tianjin heat supply company operational monitoring platform
It by when data be collected analysis, it is mean value, boundary value, accumulative by necessary data prediction, i.e. outlier processing
The filling processing of the methods of value, correlation, promotes the quality of data.It is the important foundation work in order to do subsequent data analysis.
According to professional experiences, qualitative excavation is carried out to the mode of adjustment curve, it is mixed to inquire into above-mentioned data digging method Gauss
Close Model tying outdoor temperature, secondary water-supply temperature, three features of secondary heat consumption by when sample data on application, build
Vertical three-dimensional Gaussian mixed model clustering excavates identification operational mode.Iteration is constantly updated according to model, is based on BIC information
It is optimal result to get to classification 1,2,3 that criterion result, which is clustered into 3 classes,.Cluster classification information is attached to each sample data
On, detailed step is as follows.Fig. 3 is that the secondary water-supply temperature of the classification information containing cluster changes adjustment curve with outdoor temperature, and Fig. 4 is
The secondary heat consumption of the classification information containing cluster changes adjustment curve with outdoor temperature.
Gauss hybrid models cluster realizes that Python is a kind of object-oriented, explanation type computer on python platform
Programming language, it possesses efficient advanced data structure, and can carry out Object-Oriented Programming with the mode being simple and efficient.
Its grammer is simple, graceful, and powerful is explanatory, so that it is all become an ideal language in many fields, but python is not mentioned
For a special Data analytic environment, in data analysis field, it is needed by numerous expanding libraries, to provide for python
Quick array manipulation, numerical operation are with drawing function and the tool of powerful machine learning.
And the calculating of clustering problem of the present invention, it is based on numpy, pandas, matplitlib and engineering
On the basis for practising relevant sklearn. class libraries.
Model thinking are as follows: after reading in data, outdoor temperature, secondary water-supply temperature, secondary heat consumption are extracted respectively, utilized
GaussianMixture in the library sklearn.mixture is analyzed, and Clustering Model parameter is trained.And it is repeatedly changed
In generation, obtains the degree of reliability of Log.likelihood judgment models.
The specific code of this model is as follows:
1 cluster result of table is shown
By above-mentioned cluster result, the Rule adjusting of secondary water-supply temperature, which can be excavated effectively, to be extracted, from control
Mode is discussed.By previous contents it is found that the adjusting of secondary water-supply temperature, which mainly passes through, changes a supply water temperature or primary
Circular flow is realized, draws the associated change scatter plot of first and second supply water temperature as shown in Figure 5, it can be seen that secondary water-supply
Temperature and a supply water temperature are in certain linearly related variation.It is bent by the secondary water-supply temperature adjusting clustered at each
In line classification, one, the linear degree of secondary water-supply temperature are high.Supply water temperature (boiler leaving water temperature) is an energy due to one time
Enough parameters directly actively adjusted, therefore it can be proved that secondary water-supply temperature with the changing rule of outdoor temperature is by once supplying
What the variation control of coolant-temperature gage was realized.A supply water temperature can be seen that one with the scatter plot that outdoor temperature changes as shown in Figure 6
Secondary supply water temperature, that is, boiler leaving water temperature is mainly to be adjusted according to outdoor temperature, this is further proved, secondary water-supply temperature
It is to be adjusted to realize by primary side matter with the adjustment curve of outdoor temperature.One cycle flow-time sequence dissipates according to Fig.7,
Point diagram.It can could see 2 stability of flow of mode, for a kind of secondary water-supply temperature operational mode.Operational mode 1 is primary
There is three phases changes in flow rate, i.e. the wherein ununified secondary water-supply temperature of first and second side supply water temperature linear change
Operational mode, a kind of 3 corresponding secondary water-supply temperature operational modes of flow trim fluctuation of operational mode.
(2) cluster classification information is distributed in secondary water-supply temperature-time Sequence dot plot
Cluster classification information is attached in each sample data, secondary water-supply temperature, time, cluster classification are then chosen
Cluster classification information is attached on color range item, describes secondary water-supply temperature-time sequence scatterplot by the data of three kinds of features of information
Figure, as shown in Figure 9.It is distributed on secondary water-supply temperature-time Sequence dot plot to obtain different classes of information.It can be with from figure
Find out that totally point three period In The Initial Period Of Heatings, heating mid-term, heating latter stage consider secondary water-supply Temperature Distribution.Similarly describe two
Secondary circular flow time series scatter plot, as shown in Figure 8.
(3) classifying rationally heating duration section
According to cluster classification information in secondary water-supply temperature-time Sequence dot plot distribution situation, three can be substantially divided
Period (In The Initial Period Of Heating, mid-term, latter stage), according to professional experiences, to secondary water-supply temperature adjustment curve be set for it is qualitative
It interprets.Efficiency in Buildings in Tianjin Area Heating Season starts from November 15, at heating initial stage, originally 1 day higher supply water temperature, it is therefore intended that compared with
Heating building, considers the thermal inertia of architecture noumenon, quickly increases room temperature in short time.In a period of time later, it is pair
When relative low temperature weather and morning 5~9, at night 17~23 when user is special uses heat demand.Using higher supply water temperature mould
The regulation of formula 1 improves indoor comfort degree, reduces customer complaint rate, improves the purpose of heating charge income.Therefore it is not difficult to explain, heat
There are 3 kinds of secondary water-supply temperature operational modes in initial stage.It is secondary in conjunction with the secondary flow time series scatter plot distributions of Fig. 8 and Fig. 9
Supply water temperature time series scatter plot, which can be seen that, can be divided into In The Initial Period Of Heating 15~December of November 10.
Similarly December 11~2 month can be divided into heating mid-term on 22nd, extremely also be held according to the adjusting of secondary cycle flow
Easily determine the heating mid-term period.Mainly there are two kinds of supply water temperature shaping modes in heating mid-term, wherein in January 22 days~1
The moon 24, extreme low temperature weather used higher supply water temperature mode 1, and raising indoor comfort degree reduces customer complaint rate.
2 months latter stages, 23 days~March 15 heat more consideration is given to should suitably reduce supply water temperature in heating latter stage, reaches
To the purpose for realizing energy-saving raising heat supply income.Table 2 is that the interim runing adjustment mode of heating summarizes.
The interim runing adjustment that heats of table 2 summarizes
| Regularity | Date | Primary categories |
| Without Unified Policy | 11-15/12-10 | 1、2、3 |
| Strategy | 12-11/02-22 | 1、3 |
| Strategy | 02-23/03-15 | 2 |
(4) operation reserve in different heating duration sections is identified
Three heating duration sections are individually analyzed, outdoor temp under each each operational mode of heating duration section is described
Spend-supply water temperature scatter plot, outdoor temperature-secondary water-supply temperature scatter plot and the secondary heat consumption scatterplot of outdoor temperature-
Figure and the secondary temperature difference heat consumption scatter plot of outdoor temperature-.The scatterplot that linear character is presented is fitted to linear equation form, non-linear
Feature scatterplot data statistic analysis average value standard deviation form.Unit temperature difference heat dissipation obtains curvilinear equation form by curve matching,
To obtain the operation reserve and heat dissipation mode of each period.
The analysis of In The Initial Period Of Heating (15-December 10 November) runing adjustment, mainly divides three operational modes: 1, November 15 days
When 19~on November 19 14 when, supply water temperature adjusts form, secondary water-supply temperature adjusts form, and secondary heat consumption changes shape
Formula, unit temperature difference heat consumption version is as shown in Figure 10-1~Figure 10-4, and secondary cycle stability of flow is in 229~238m3/h。
2, November 22 0 when~December 1 18 Shi Yici supply water temperature adjust form, secondary water-supply temperature adjust form, secondary heat dissipation
Measure version, unit temperature difference heat consumption version as shown in Figure 11-1~Figure 11-4, secondary cycle stability of flow 225~
237m3/h.3, when 21 days 23 15 whens~November of November 19 and when 9 days 23 0 when~December December 2 and its relative low temperature day
When gas, morning 5~9, at night 17~23 when it is special use heat demand time point, supply water temperature adjusts form, secondary water-supply temperature
Degree adjusting form, secondary heat consumption version, unit temperature difference heat consumption version are secondary as shown in Figure 12-1~Figure 12-4
Circular flow in two stages stablize in 229~238m by early period3/ h, 237~245m of later period3/h。
Heat the analysis of mid-term (on December 22-2 months on the 11st) runing adjustment, is mainly divided to two operational modes: 1, January 22 days 0
When~on January 24 23 when and its individual requirement of low temperature sections,
Supply water temperature adjusts form, secondary water-supply temperature adjusts form, secondary heat consumption version, the unit temperature difference
Heat consumption version is as shown in Figure 13-1~Figure 13-4, and secondary cycle stability of flow is in 239~246m3/h.2, mid-term other
All Time, a supply water temperature adjusts form, secondary water-supply temperature adjusts form, secondary heat consumption version, unit temperature
Poor heat consumption version as shown in Figure 14-1~Figure 14-4, secondary cycle flow in two stages, stablize early period 225~
235m3/h.Later period is in 245~225m3/ h is reduced in stepped.
Heat the analysis of latter stage (2 months 23-March 15) operation reserve, and mainly supply water temperature adjusts form, secondary
Supply water temperature adjusts form, secondary heat consumption version, unit temperature difference heat consumption version such as Figure 15-1~Figure 15-4 institute
Show.Secondary cycle stability of flow is in 160~170m3/h.Each heating duration section operation reserve and heat dissipation mode are summarized in 3 institute of table
Show.
(5) secondary side runing adjustment tactical comment
According to the operation reserve and heat dissipation mode of each stage identification in front.According to supply water temperature, whether correlation operation is adjusted
The different form and heat consumption of section, unit temperature difference heat consumption data characteristics metrics evaluation operation reserve and energy potential evaluation.In detail
Details condition is summarized in shown in table 4.It can could see, In The Initial Period Of Heating energy-saving potential is maximum, reaches the stage total heat dissipation value
15.53% (about 207525kw.h) payes attention to supply water temperature according to outdoor temperature correlation runing adjustment, and considers moment and low
Wet waits runing adjustment stage by stage.Heating mid-term reaches 6.46% (about 242472kw.h) energy-saving potential of the stage total heat dissipation value
Moderate but amount of energy saving is maximum, considers adjustment linear dependence strategy, linear adjustment equation slope, intercept.And according to outdoor temp
Degree size can set runing adjustment equation stage by stage, such as: -10 DEG C~-5 DEG C, 0 DEG C~10 DEG C, 10 DEG C or more are formulated respectively
Supply water temperature operation regulation curve.The heating later period reaches 0.2% (about 1657kw.h) of the stage total heat dissipation value, and energy-saving potential is small
But divergence indicator value 60.12% is bigger than normal, is primarily due to that the heating later period temperature difference is big, and outdoor temperature is higher than 10 DEG C of time point
It is more.What it is with greater need for consideration is that can set runing adjustment equation stage by stage according to outdoor temperature size.It can guarantee for thermal balance,
It improves heat supply satisfaction and reaches energy saving in running purpose.
The present invention is not limited to embodiments described above.Above the description of specific embodiment is intended to describe and say
Bright technical solution of the present invention, the above mentioned embodiment is only schematical, is not restrictive.This is not being departed from
In the case of invention objective and scope of the claimed protection, those skilled in the art may be used also under the inspiration of the present invention
The specific transformation of many forms is made, within these are all belonged to the scope of protection of the present invention.
3 heat exchange station runing adjustment strategy of table detailed description summarizes
4 heat exchange station runing adjustment tactical comment of table detailed description summarizes
Claims (6)
1. a kind of runing adjustment strategy identification and evaluation method that heat exchange station is general, characterized in that the following steps are included:
Step (1): operation data gauss hybrid models are clustered；Select heating season by when outdoor temperature, secondary water-supply temperature, two
The data of secondary three kinds of features of heat consumption cluster its scatterplot data application multidimensional gauss hybrid models；
Step (2): the secondary water-supply temperature-time Sequence dot plot distribution of the classification information containing cluster is obtained；By the way that classification will be clustered
Information is attached to color range item, is applied to secondary water-supply temperature-time Sequence dot plot；It is corresponding to obtain heating season various time points
Secondary water-supply temperature runing adjustment mode, one kind are one mode；
Step (3): heating duration section is divided；The characteristics of being clustered according to secondary water-supply temperature-time Sequence dot plot；Exchange heat stations
2~4 heating periods of heating season point；
Step (4): the operation reserve and heat dissipation mode in each heating period are identified；To each heating period operation reserve and heat dissipation
Cluster classification information is attached in each sample data, and is applied to-supply water temperature scatterplot of outdoor temperature by pattern analysis
The secondary temperature difference consumption of figure, outdoor temperature-secondary water-supply temperature scatter plot, the secondary heat consumption scatter plot of outdoor temperature-, outdoor temperature-
Heat scatter plot obtains the heat exchange station operation reserve and heat dissipation mode under outdoor temperature reset feature；
Step (5): secondary side runing adjustment tactical comment；Linear character or data system based on the secondary heat consumption of outdoor temperature-
Characteristic evaluating secondary side operation reserve is counted, the data statistical characteristics based on the secondary temperature difference heat consumption of outdoor temperature-evaluate secondary side
Operation reserve calculates fractional energy savings, amount of energy saving, divergence indicator by setting temperature difference heat consumption a reference value, evaluates secondary operation reserve
Energy-saving potential and heat dissipation departure degree.
2. identification and evaluation method according to claim 1, it is characterized in that: to operation data Gaussian Mixture mould in step (1)
Type cluster, is described as follows:
1) mathematical algorithm of mixture-of-Gaussian mode (GMM) cluster is summarized as follows, and data matrix is defined as X=[X1, X2..., Xd]T,
Calculate joint probability distribution:
Wherein: X=[X1, X2..., Xd]T, wherein d indicates that array dimension, K are the number of mixed Gauss model, αkFor Gauss at
The weight coefficient divided, 0 < αk< 1,φk(xi|μk, ∑k) it is k-th of Gauss model, μkAnd ∑kIt is respectively high
The mean value and variance of this model, and p (X | θ) it is likelihood probability of the array X under mixed Gauss model；γjkAccording to { αk, μk, ∑k}
Determine one group of { αk, μk, ∑kGauss model parameter value calculation posterior probability, L (θ | X) is maximum likelihood probability value；Gauss is mixed
The training process of molding type is to solve parameter set { αk, μk, ∑k}；The optimization method used is Expectation
Maximization (EM) algorithm, is divided into two steps:
E step: pass through one group of given { αk, μk, ∑kValue, calculate posterior probability γjk；
M step: posterior probability γ is calculated by E stepjk, calculate one group of new { αk, μk, ∑kValue；
The E that iterates step and M step, until obtaining maximum likelihood value L (θ | X), termination obtains final result,
2) choose heat exchange station operation data in outdoor temperature, secondary water-supply temperature, three features of secondary heat consumption by when sample
Notebook data realizes three-dimensional Gaussian mixed model clustering on python platform.
3. identification and evaluation method according to claim 1, it is characterized in that: obtaining the classification information containing cluster in step (2)
The distribution of secondary water-supply temperature-time Sequence dot plot, the specific steps are as follows:
Cluster classification information is attached in each sample data, it is rear to choose secondary water-supply temperature, moment, cluster classification information three
Cluster classification information is attached on color range item, describes secondary water-supply temperature-time Sequence dot plot, obtain by kind feature samples data
It is distributed on secondary water-supply temperature-time Sequence dot plot to different classes of information.
4. identification and evaluation method according to claim 1, it is characterized in that: dividing the specific of heating duration section in step (3)
Steps are as follows:
It is distributed on secondary water-supply temperature-time Sequence dot plot according to different classes of information, chooses one section that scatterplot classification is concentrated
Time divides；Exchange the entire heating season of heat stations point 2~4 heating duration sections, heat exchange station is in order to meet Daily minimum temperature and spy
It fixes time a section heat demand, needs to be adjusted according to actual characteristic, will appear 1~3 kind of secondary confession in divided heating duration section
There are 2~3 operational modes in coolant-temperature gage operational mode, In The Initial Period Of Heating, and heating mid-term 1~2 mode occurs, heats 1~2 kind of latter stage
Mode.
5. identification and evaluation method according to claim 1, it is characterized in that: identifying the operation of each heating period in step (4)
Strategy and heat dissipation mode, the specific steps are as follows:
To each heating period independent analysis, the i.e. different classification of operational mode all under each heating period is depicted；It will gather
Class classification information is attached in each sample data, and is applied to outdoor temperature-supply water temperature scatter plot, an outdoor temperature-
The secondary heat consumption scatter plot of secondary water-supply temperature scatter plot, outdoor temperature-, the secondary temperature difference heat consumption scatter plot of outdoor temperature-；It is in
The scatterplot of existing linear character is fitted to linear equation form, and nonlinear characteristic scatterplot data statistic analysis obtains mean value, standard deviation
Form；Wherein the secondary temperature difference heat consumption scatter plot of outdoor temperature-is fitted to curvilinear equation and data statistics obtains mean value, standard
Poor form；To realize all operational mode qualitative description of each heating period, obtain that a kind of heat exchange station is general to be can recognize
The operation reserve and heat dissipation mode based on outdoor temperature qualitative description.
6. identification and evaluation method according to claim 1, it is characterized in that: secondary side runing adjustment strategy is commented in step (5)
Valence, the primary side that step (4) is identified according to the secondary heat consumption mode of identification, unit temperature difference heat consumption mode, secondary side fortune
Row strategy is evaluated, the specific steps are as follows:
1) linear equation form or nonlinear characteristic statistical data (mean value, standard based on the secondary heat consumption mode of outdoor temperature-
Difference) evaluation secondary side operation reserve；
2) based on outdoor temperature-unit temperature difference heat consumption mode curvilinear equation form spy and data statistical characteristics (mean value, mark
It is quasi- poor) evaluation secondary side operation reserve；
3) set unit temperature difference heat consumption benchmark, with reference to the intercept of temperature difference heat consumption Mode Equation, calculate by when operation data base
Quasi- heat consumption；To calculate fractional energy savings, the amount of energy saving, divergence indicator under each heating duration section each pattern；To operational mode
Energy-saving potential and heat dissipation departure degree；Divergence indicator calculation formula is as follows:
In formula: δ-divergence indicator, x0Benchmark heat consumption, xjPractical heat consumption, N- sample data number.
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